Validation of a Fully Automated Hybrid Deep Learning Cardiac Substructure Segmentation Tool for Contouring and Dose Evaluation in Lung Cancer Radiotherapy.

Journal: Clinical oncology (Royal College of Radiologists (Great Britain))
Published Date:

Abstract

BACKGROUND AND PURPOSE: Accurate and consistent delineation of cardiac substructures is challenging. The aim of this work was to validate a novel segmentation tool for automatic delineation of cardiac structures and subsequent dose evaluation, with potential application in clinical settings and large-scale radiation-related cardiotoxicity studies.

Authors

  • V Chin
    University of New South Wales, South Western Sydney Clinical School, Sydney, Australia; Ingham Institute for Applied Medical Research, Radiation Oncology, Sydney, Australia; Department of Radiation Oncology, Liverpool and Macarthur Cancer Therapy Centres, Sydney, Australia. Electronic address: vicky.chin@unsw.edu.au.
  • R N Finnegan
    Ingham Institute for Applied Medical Research, Radiation Oncology, Sydney, Australia; School of Physics, Institute of Medical Physics, University of Sydney, Sydney, Australia; Northern Sydney Cancer Centre, Royal North Shore Hospital, St Leonards, Australia.
  • P Chlap
    University of New South Wales, South Western Sydney Clinical School, Sydney, Australia; Ingham Institute for Applied Medical Research, Radiation Oncology, Sydney, Australia; Department of Radiation Oncology, Liverpool and Macarthur Cancer Therapy Centres, Sydney, Australia.
  • J Otton
    University of New South Wales, South Western Sydney Clinical School, Sydney, Australia; Department of Cardiology, Liverpool Hospital, Sydney, Australia.
  • A Haidar
    University of New South Wales, South Western Sydney Clinical School, Sydney, Australia; Ingham Institute for Applied Medical Research, Radiation Oncology, Sydney, Australia; Department of Radiation Oncology, Liverpool and Macarthur Cancer Therapy Centres, Sydney, Australia.
  • L Holloway
    University of New South Wales, South Western Sydney Clinical School, Sydney, Australia; Ingham Institute for Applied Medical Research, Radiation Oncology, Sydney, Australia; Department of Radiation Oncology, Liverpool and Macarthur Cancer Therapy Centres, Sydney, Australia; School of Physics, Institute of Medical Physics, University of Sydney, Sydney, Australia.
  • D I Thwaites
    School of Physics, Institute of Medical Physics, University of Sydney, Sydney, Australia; Radiotherapy Research Group, Leeds Institute of Medical Research, St James's Hospital and University of Leeds, Leeds, UK.
  • J Dowling
    University of New South Wales, South Western Sydney Clinical School, Sydney, Australia; School of Physics, Institute of Medical Physics, University of Sydney, Sydney, Australia; CSIRO, Australian e-Health and Research Centre, Herston, Australia.
  • G P Delaney
    University of New South Wales, South Western Sydney Clinical School, Sydney, Australia; Ingham Institute for Applied Medical Research, Radiation Oncology, Sydney, Australia; Department of Radiation Oncology, Liverpool and Macarthur Cancer Therapy Centres, Sydney, Australia.
  • S K Vinod
    University of New South Wales, South Western Sydney Clinical School, Sydney, Australia; Ingham Institute for Applied Medical Research, Radiation Oncology, Sydney, Australia; Department of Radiation Oncology, Liverpool and Macarthur Cancer Therapy Centres, Sydney, Australia.